Identifying clinical and psychological correlates of persistent negative symptoms in early-onset psychotic disorders
Bibliographic record
Abstract
Persistent negative symptoms (PNS) contribute to impairment in psychosis. The characteristics of PNS seen in youth remained under-investigated. We aimed to demonstrate clinical, treatment-related, and psychosocial characteristics of PNS in early-onset schizophrenia-spectrum disorders (EOSD). 132 patients with EOSD were assessed with Positive and Negative Symptom Scale, Brief Negative Symptom Scale, Calgary Depression Scale for Schizophrenia, and Simpson-Angus Scale. Parenting skills and resilience were evaluated using Parental Attitude Research Instrument and Child and Youth Resilience Measure-12. Longer duration of untreated psychosis (DUP) and prodromal phase were found in primary and secondary PNS groups, compared to the non-PNS group. The primary PNS group was characterized by earlier age-onset, lower smoking rates, and more common clozapine use. Resilience and egalitarian/democratic parenting were negatively correlated with symptoms related to motivation/pleasure and blunted expression. More blunted expression-related symptoms and longer DUP in the first episode significantly predicted primary/secondary PNS at follow-up. Using the data from total negative symptom scores and DUP, Receiver Operating Characteristic analyses significantly differentiated primary/secondary PNS groups from the non-PNS counterparts. PNS associated with blunted expression and low motivation/pleasure in the first episode could persist into clinical follow-up. Effective pharmacological treatment and psychosocial interventions are needed in youth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".